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undomesticated and feral urban animals. Through ethnographic fieldwork and archival studies in Denmark, Sweden and Norway, we follow the technological development and legislation on animal rights in the EU since
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thereafter. The PhD project will focus on developing and testing AI-assisted computational workflows for predictions of both ground- and excited-state material properties, with applications spanning
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Network funded by the European Union. As a Doctoral Candidate in MET2ADAPT, you will focus on developing a robust framework for uncertainty quantification (UQ) and technology qualification, aimed
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through online surveys and interviews, prototype development for accessible setup and operation of nanoservers (both on web and mobile platforms), and longitudinal evaluation of the prototypes through live
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maintenance planning framework for wind turbine technologies, with a focus on enhancing structural resilience and operational efficiency. Key objectives include the development of a tailored risk-based
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is to develop RL methods that can search large policy spaces and support decision-makers in exploring robust strategies under deep uncertainty. Policy problems typically involve many control levers
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, acoustic, and archival). Your primary tasks will be: Development of new research projects in collaboration with colleagues at the DTU Aqua sections and/or international partners. Publication of papers in
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archival). Your primary tasks will be: Development of new research projects in collaboration with colleagues at the DTU Aqua sections and/or international partners. Publication of papers in peer reviewed
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develops predictive, multi-scale computational frameworks to guide sustainable microbial food production. By coupling data science with mechanistic models, this collaboration between universities, research
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of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD project falls under the collaboration between